Since the turn of the last century, biological networks have been one of the most widely used mathematical models employed in systems biology to uncover complex relationships from raw omics data. In particular protein pro- tein interaction networks (PPINs) are often used to predict putative protein complexes and uncover the functional modular structure of the cell's proteomic machinery. In this survey we give an overview of density based algorithms for community detection in biological networks (mainly PPINs) which is a popular approach to network analysis, complementary to network clustering. We then touch on recent research direction involving biological data integration, network dynamization, and extensions to dierent types of biological networks.

Community Detection in Biological Networks

Marco Pellegrini
2018

Abstract

Since the turn of the last century, biological networks have been one of the most widely used mathematical models employed in systems biology to uncover complex relationships from raw omics data. In particular protein pro- tein interaction networks (PPINs) are often used to predict putative protein complexes and uncover the functional modular structure of the cell's proteomic machinery. In this survey we give an overview of density based algorithms for community detection in biological networks (mainly PPINs) which is a popular approach to network analysis, complementary to network clustering. We then touch on recent research direction involving biological data integration, network dynamization, and extensions to dierent types of biological networks.
2018
Istituto di informatica e telematica - IIT
bioinformatics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/371047
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